Effect of lipid extraction on the interpretation of fish community trophic relationships determined by stable carbon and nitrogen isotopes
Bibliographic record
Abstract
Stable isotopes of carbon (C) and nitrogen (N) are commonly used to evaluate trophic relationships and food web structure; however, the decision to extract lipids or not may influence the interpretation of results. Lipid extraction is not a universal practice, thus pooling or comparing results across studies may not always be appropriate. Additionally, common lipid extraction techniques remove not only lipids, but also N-containing compounds that may alter the δ15N value of a sample. We examined differences in the interpretation of fish community trophic structure derived from δ13C and δ15N stable isotope data based on lipid-extracted and nonextracted samples from nine freshwater fish species. Lipid extraction significantly increased δ13C and δ15N, causing a positive shift in overall food web placement. The magnitude of isotopic change did not, however, differ among species, such that the overall interpretation of the fish community structure was not altered. The consistent increase in both C and N isotopes did, however, significantly alter the placement of the food web in coordinate space relative to nonextracted webs. Cross-study comparisons need to consider these procedural inconsistencies when drawing conclusions from multiple studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".